Hydrology of the Delta Marsh Watershed: water balance characterization and analysis of land use changes
Bibliographic record
Abstract
A hydrological model was used to examine the water balance of the Delta Marsh Watershed (DMW) currently and as impacted by land use changes. Understanding DMW hydrology can help to improve conditions in the Delta Marsh. MIKE SHE model results showed that the water balance is typical of prairie conditions with limited wintertime activity, significant spring melt runoff, and high summertime evapotranspiration and infiltration. Results showed that the DMW contributes approximately 40 million m3 of water to the Delta Marsh in an average year, or 710 m3/ha/yr. Portage Creek is the single greatest inflow from the watershed (31% of total) and the West Marsh area also receives large runoff volumes (combined 37% of total). Analysis of land use changes showed that urban expansion in the DMW would increase annual marsh inflows by over 50% under one urbanization scenario due to associated decreases in infiltration and transpiration. An agricultural shift towards row crop predominance would have minimal impact on the DMW water balance. Conversion of cropland to natural vegetation would decrease annual runoff by 12% to the marsh due to increased surface ponding, infiltration, and transpiration.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".